Assessing the level of awareness in patients suffering from disorders of consciousness (DOC) as a result of traumatic injury, strokes, or degenerative diseases remains a central challenge of modern neurology. Current estimates suggest that misdiagnosis occurs in over 40% of patients. This high rate of diagnostic error may partially be explained by the fact that clinicians are currently forced to make inferences about a patient's awareness based solely on overt responses to verbal commands obtained at a patient's bedside, which can be restricted by factors such as cognitive dysfunction, aphasia, motor impairment or tracheotomy. Development of brain activity markers of consciousness holds promise for improving diagnostic accuracy. One of the most important clinical goals is to assess whether an individual is aware of herself and her state (referred to as reflective consciousness (RC)), which is critical to making appropriate therapeutic choices and in determining prognosis. Preliminary studies in healthy adults have shown that RC is associated with activity within a network of frontoparietal (FP) cortices. Consistent with this, patients with presumed global loss of consciousness, such as the unresponsiveness wakefulness syndrome (vegetative state) and certain forms of anesthesia-induced unresponsiveness, have decreased activity in FP cortices. However, alterations in regional activity within FP cortices are insufficient as an unambiguous marker of consciousness because activation in these regions is also observed during unconscious states. Recent findings suggest that a potentially more sensitive marker of global unconsciousness may be a reduction of top-down FP functional connectivity. These findings converge with recent theoretical work and computational modeling, which has suggested a link between consciousness and neural effective connectivity. However, a direct link between RC and top-down FP effective connectivity has yet to be established. The proposed studies use a multimodal approach across two different arousal states to investigate the relationship between RC and FP directional connectivity. We will first examine changes in directional connectivity by applying state-of-the-art measures of Granger Causality (GC) and Dynamic Causal Modeling (DCM) to [high-density electroencephalography (hd-EEG)]. We will then directly assess changes in neural effective connectivity using TMS/hd-EEG to directly perturb targeted neural populations and model changes in neural signal propagation from FP regions. Using this multimodal approach, Aim 1 will examine how modulation of RC during waking influences directional connectivity in FP cortices. Aim 2 will then examine the directional connectivity changes that are associated with loss of RC in REM sleep. Together, we expect that these studies will help establish a brain activity marker for RC that does not depend on an individual's ability to communicate or respond to sensory signals. Identification of such a marker has the potential to both improve diagnostic accuracy as well as extend basic scientific understanding of these disorders, opening new avenues for treatment.